Evidence map›Paper›PMID 31416262›Full record

ArticleInternational journal of environmental research and public health2019

A Linguistic Hierarchy Model with Self-Confidence Preference Relations and Its Application in Co-Regulation of Food Safety in China.

Sha Fan, Hengjie Zhang, Huali Tang

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Sha FanBusiness School, Sichuan University, Chengdu 610065, China.
Hengjie ZhangBusiness School, Hohai University, Nanjing 211100, China. hengjiezhang@hhu.edu.cn.
Huali TangBusiness School, Sichuan University, Chengdu 610065, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Linguistic preference relations are widely used by decision makers to elicit their preferences over alternatives in the Group Decision Making (GDM) process. Recent studies have shown that self-confidence, as an important human psychological behavior, has an important influence on decision-making results. However, multiple self-confidence levels of decision makers are seldom considered in the linguistic preference relation. Meanwhile many real-word decision-making problems are analyzed in a hierarchical structure, in which a complicated problem can be divided into several easier comprehended sub-problems. Hence, this paper aims at designing a linguistic hierarchy model with self-confidence preference relation (LHM-SCPR) to discuss complex GDM problems in a hierarchical structure. In the SC-LPR, each element contains two components, the first one is the preference value between pairs of alternatives, and the second one that is defined on a linguistic term set represents decision maker's self-confidence level associated to the first component. Meanwhile, a nonlinear programming model is proposed to derive individual preference vector from SC-LPR. Then, we apply LHM-SCPR in co-regulation of food safety to present the validity of this method, and find that improving the participation skills regarding co-regulation of food safety is the most pressing task. Finally, detailed comparative analysis and discussion are presented to verify the validity of the proposal.

Indexed as

AlgorithmsDecision MakingLinguisticsSelf ConceptChinaFood LabelingFood SafetyFuzzy LogicHumansco-regulation of food safetygroup decision makinghierarchical structurelinguistic preference relationsnonlinear programming modelself-confidence

Identifiers

PMID31416262
PMCPMC6719042

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